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Journal Pre-proofs
COVID-19 and suburban public transport in the conditions of the Czech Re‐
public
Petr Fridrisek, Vit Janos
PII: S2590-1982(21)00228-1
DOI: https://doi.org/10.1016/j.trip.2021.100523
Reference: TRIP 100523
To appear in: Transportation Research Interdisciplinary Per‐
spectives
Received Date: 23 August 2021
Revised Date: 29 November 2021
Accepted Date: 13 December 2021
Please cite this article as: P. Fridrisek, V. Janos, COVID-19 and suburban public transport in the conditions of the
Czech Republic, Transportation Research Interdisciplinary Perspectives (2021), doi: https://doi.org/10.1016/
j.trip.2021.100523
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© 2021 The Author(s). Published by Elsevier Ltd.
COVID-19 and suburban public transport
in the conditions of the Czech Republic
Petr Fridrisek1*, Vit Janos2
1Department of Logistics and Management of Transport, Czech Technical University in Prague,
Faculty of Transportation Sciences, Konviktská 20, 110 00 Prague, Czech Republic. Email:
fridrisek@fd.cvut.cz
2Department of Logistics and Management of Transport, Czech Technical University in Prague,
Faculty of Transportation Sciences, Konviktská 20, 110 00 Prague, Czech Republic. Email:
janos@fd.cvut.cz
* Correspondence: fridrisek@fd.cvut.cz
ABSTRACT
This article focuses on possible approaches to safe regional public transport during the COVID-19
pandemic. The purposes of the research are examination the conditions for ensuring safe transport and
the impact on the planning of transport services. The result is an assessment of the operation of regional
public transport, consisting of the possibility of maintaining safe distances in public transport. Authors
work on suburban transport cases in selected regions of the Czech Republic (Prague and Moravian-
Silesian Region). Census devices in public transport, periodical transport surveys, Google mobility
reports and data on fare sales from regional transport were used as data sources. Emphasis is placed on
a safe distance between commuters, this condition leads to lower occupancy of the vehicle while
maintaining the capacity of the vehicles. The value of this new occupancy is determined for selected
vehicles and the coefficient that represents the maximum occupancy level to ensure safe transport is
established. The capacity of the connections is examined in the period before and during the COVID-19
pandemic. Compared to the period before COVID-19, the daily variation of passengers is expected to
change significantly, leading to different occupancy rates during the day.
KEYWORDS:
passenger transport; integrated transport systems; timetable design; travel demand; COVID-19
pandemic; vehicle capacity
1. Introduction
COVID-19 has unprecedentedly influenced everyday life in many areas. Public transport systems have
responded differently to this unpredictable change, but the aim of all these approaches has been the
same - to ensure the safe transport of passengers. The motivation for the research is examination the
conditions for ensuring safe transport included the impact on the planning of transport services (Bucsky,
2020, Gkiotsalitis and Cats, 2021). The pandemic has had a major impact on public transport. Many
passengers stopped using public transport temporarily (partial transitions to homeoffice), some
permanently (concerns about their health, risk of infection, transition to car driving). If public transport
is to be a long-term safe and sustainable transport mode, it must deal with these risks and be able to
face current challenges (Bucsky, 2020).
1.1. COVID-19 and its relation to public transport
Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most
people infected with the COVID-19 virus have a respiratory illness, vulnerable people (older people,
chronically ill people) belong to the risk group of the most endangered persons (World Health
Organization, 2021).
There are three frequently accepted modes of viral transmission: via small airborne droplets (aerosols),
via larger airborne droplets, and contact with a contaminated surface (Morawska et al., 2020). The best
way to prevent and slow down the transmission of COVID-19 is to follow three basic rules: the
protection of the nose and mouth using a mask, washing and disinfection of the hands, and the
observance of safe distances to limit the spread of droplet infection. According to various studies and
expert opinions, a distance in the range of 1.5 - 2 meters can be set as a safe distance (CDC, 2021a).
Given the worldwide reputation of COVID-19, the authors consider that there is no need to recapitulate
the general rules for handling the COVID-19 pandemic. Likewise, in the context of this article, authors do
not consider it essential from a physical and medical point of view to describe the exact procedures by
which droplets spread in the air and subsequently enter the body of prospectively infected persons. The
following chapters will discuss the impacts of measures related to the protection against COVID-19 on
public transport, the spread of COVID-19 in public transport and will propose specific measures in public
transport to create a safe and credible environment (De Vos, 2020).
2. Methods
For better understanding of travel behavior and conditions prevailing during transport, the mobility
analysis was carried out (Pawar et al., 2020, Gaskin et al., 2021). The capacity of the connections is
examined, and the relative occupancy for specific sections and time slots in the period before and during
the COVID-19 pandemic is assessed. Emphasis is placed on a safe distance between commuters, this
condition leads to a significant reduction in the maximum occupancy of vehicles (Muller et al., 2020).
This creates a new value that can be described as the maximum number of passengers to ensure safe
transport in the spread of respiratory diseases. The coefficient that represents the maximum occupancy
level to ensure safe transport is established.
The changes in mobility caused by the COVID-19 pandemic have had a significant impact on public
funds. Public transport is standardly financed from fare revenues and finances (compensations) from
public service obligations (PSO).
Figure 1 captures the relation between the revenue and the expenditure components.
Figure 1. Illustrated scheme of costs, revenues, and compensations in field of public transport (Source:
authors)
The Figure 1 is divided into five parts, each describing a different case in terms of vehicle capacity
utilization. The situation before the COVID-19 pandemic is shown on the left. The following columns
describe the conditions during the COVID-19 pandemic, always emphasizing the observance of safe
distances during transport.
Left column of the pair: fuels and all costs related to the volume of transport performance are the
variable cost (red part of the column), and depreciation of vehicles and all costs related to the duration
of the contract (PSO) are fixed costs (orange and yellow parts of the column).
Right column of the pair: compensation (in the term of PSO – public service obligation) means financial
compensation to the carrier, which aims to subsidize traffic in order to provide transport in the public
interest. Additional compensation means an increase in revenue related to the incurrence of additional
costs or loss of sales.
The second pair of columns represents a situation, when there has been significant drop in passenger
demand and the vehicle capacity is shortened. The additional compensation covers the loss of fare
revenue reduced by variable cost.
The third pair of columns represents a situation, when there has been moderate decrease of passengers.
The existing vehicle capacity is sufficient to ensure safe distances. The additional compensation only
covers the loss of fare revenue.
The fourth pair of columns represents a situation, when there has been moderate decrease of
passengers. The existing vehicle capacity is insufficient to ensure safe distances, minor strengthening of
capacity is needed. The additional compensation covers the loss of fare revenue and capacity
strengthening.
The last pair of columns represents a situation, when there has been no decrease of passengers
(mobility is on the same level as before COVID-19 pandemic). The existing vehicle capacity is absolutely
insufficient to ensure safe distances, major strengthening of capacity is necessary. The additional
compensation covers the capacity strengthening. Significant capacity strengthening is threatened by
infrastructure limits and the availability of the necessary number of vehicles for capacity strengthening.
2.1. Measures on public transport in connection with COVID-19
Much has been written about the basic rules for reducing coronavirus transmission, but there are still
only a few studies that are focused on the specific spread of COVID-19 in public transport vehicles.
Public transport vehicles are relatively confined and there is a higher density of passengers who usually
travel for longer than 15 minutes. The basic rules are set out by the Centers for Disease Control and
Prevention on their website, where the recommendations related to public transport are described in
detail (CDC, 2021b):
• If possible, consider traveling during non-peak hours when there are likely to be fewer people;
• Follow physical distancing guidelines by staying at least 6 feet (about 1.83 meters) from people
who are not from your household;
• Consider skipping a row of seats between yourself and other riders if possible;
• Enter and exit buses through rear entry doors if possible;
• As much as possible, limit touching frequently touched surfaces such as kiosks, digital interfaces
such as touchscreens and fingerprint scanners, ticket machines, turnstiles, handrails, restroom
surfaces, elevator buttons, and benches;
• Use touchless payment and no-touch trash cans and doors when available;
• Exchange cash or credit cards by placing them in a receipt tray or on the counter rather than by
hand, if possible;
• Do not eat or drink on public transit;
These recommendations are a cornerstone for achieving the safe and credible environment in public
transport (Tirachini and Cats, 2020). These principles are the starting point for specific measures in
public transport, which are furthermore supported by a study of the spread of coronavirus in highspeed
trains in China (Hu et al., 2021), a study on the spread of coronavirus in New York subway network
(Harris, 2020) and a study aimed at spreading COVID-19 in the urban bus (Zhang et al., 2021).
Table 1. The attack rate is defined as the percentage of coronavirus disease 2019 cases in close contact
with index patients on the train. The numbers in parentheses are the 95% confidence interval of the
attack rate (Hu et al., 2021).
The conclusions of this study show that the probability of infection is approximately ten times higher
within one row of seats than between individual rows. The probable effect is the separation of individual
rows by tall backrests, as well as a higher risk of close contact when moving from the window seat to the
aisle accompanied by touches on the armrests on adjacent seats. Other risks may be transmitted in
common areas of the train (toilets, aisles) or the train staff may transmit the virus, but this in-fluence
and its share are difficult to demonstrate (Hu et al., 2021).
The urban bus study dealt with modeling the spread of aerosols in an urban bus in many model
situations, e.g. taking into account vehicle ventilation by opening doors, ventilation windows, or the
effect of wearing masks. The amount of penetration of particles into the passenger's respiratory system
Rows Apart
Columns Apart
Same
Column
1
2
3
4
5
Average
Same row
…
3.53 (2.89–4.31)
1.65 (1.18–2.31)
0.38 (.18–.78)
0.38 (.19–.79)
0.29 (.10–.85)
1.53 (1.30–1.80)
1
0.21 (.11–.38)
0.24 (.14–.41)
0.14 (.06–.32)
0.09 (.03–.25)
0.03 (.00–.16)
0.05 (.00–.30)
0.14 (.10–.20)
2
0.25 (.14–.45)
0.17 (.09–.33)
0.23 (.12–.46)
0.16 (.07–.36)
0.09 (.03–.27)
0.17 (.06–.50)
0.18 (.13–.25)
3
0.05 (.01–.18)
0.05 (.01–.17)
0.13 (.05–.33)
0.10 (.03–.30)
0.10 (.03–.30)
0.06 (.00–.36)
0.08 (.05–.13)
Average
0.17 (.12–.26)
0.68 (.56–.81)
0.41 (.31–.54)
0.16 (.1–.25)
0.12 (.07–.20)
0.13 (.06–.25)
0.32 (.28–.36)
was observed. The conclusions of the study show that ventilation and regular opening of the doors have
a positive effect on reducing the concentration of infected particles in the bus environment. There is an
increased risk of infection only for passengers who are close to the air outlets of the vehicle. If the driver
opens a ventilation window, it increases his risk of infection. With the proper wearing of surgical masks,
almost complete protection against the infection can be achieved for 15 minutes of virus exposure
(Zhang et al., 2021).
The study connected to New York subway network describes the effect of coronavirus spread in relation
to the limited operation of metro lines. The study concludes, among other things, that there is a link
between the spread of coronavirus and the reduction of traffic, and it would be appropriate to double or
triple the volume of traffic to alleviate the pandemic.
2.2. Mobility during COVID-19 restrictions
Public transport is an integral part of the mobility of the future, and the return of passengers to
individual transport is a step back, and it will be necessary to reexpend energy and resources to change
the modal split in favor of public transport (Drábek and Pospíšil, 2018).
A state of emergency has been declared in the Czech Republic and restrictions have been introduced to
reduce the number of physical contacts. These restrictions had a significant impact on the decline in
mobility in the first wave of the pandemic (March 2020), in the second wave of the pandemic
(November 2020) and in the third wave of the pandemic (March 2021).
This decline in population mobility can be observed in several published data, and the trend is
comparable across the Czech Republic and other European countries, such as Poland (Wielechowski,
2020). Based on the data of mobile network operators or users of the Waze application in the second
largest city in the Czech Republic (Brno), it is evident that in the first weeks after the outbreak of the
pandemic, mobility dropped sharply 60-70% within 7 days (Macioszek et al., 2017, Data.Brno, 2021).
Data from counting facilities in the Prague metro network was used as a comparison, and the number of
passengers dropped sharply by 80% within 7 days of the outbreak of the pandemic. Data about
passengers were provided by the Prague organizer of public transport - the company ROPID (Ropid,
2021). Both dramatic declines of mobility clearly show that the population did not take the pandemic
lightly and led to a truly unprecedented break of travel demand. This decline has been exacerbated by
fears of public transport.
The second wave of the pandemic is also accompanied by a decline in mobility. The second phase
culminated in the first half of November 2020 Given the less stringent measures, the number of
passengers in the Prague metro fell by 67% compared to the average number of passengers in the pre-
pandemic period. COVID-19 (Ropid, 2021).
In the third wave of the pandemic, the most stringent measures were formally introduced. The number
of passengers in the metro network fell by 68% compared to the average number of passengers at the
beginning of March 2020 (before the COVID-19 pandemic). The decrease in the number of passengers is
comparable to the decrease in the number of passengers in the second phase of the pandemic in
November 2020.
Data from March 2021 also include the use of urban bus and tram transport. Both modes of transport
reduced by 63% year-to-year. Globally, in the first decade of March 2021, the number of passengers in
public transport in Prague decreased by 64.8% compared to the period before the COVID-19 pandemic
(Ropid, 2021).
For the comparison between the capital and regional centers, a comparison of mobility through the
Google mobility report was made (Noland, 2021, Wagner et al., 2020). The comparison was made on the
basis of data from the first and third waves of the COVID-19 pandemic, using reports from 29.3.2020
(Google, 2020) and 20.3.2021 (Google, 2021). Both reports are influenced by declaring a state of
emergency and countrywide lockdown of schools, the vast majority of services, shops, and leisure
activities. The reports are not comparable, as Google modified the methodology for calculating some
variables during the processing of mobility reports. Table 1 shows the relative changes in user behaviour
compared to their usual activities, which Google defines for the period from January 3 to February 6,
2020. Relative changes in user movement are processed for each destination or location occurrence in
Table 1, considering the number of occurrences and the time spent in the locality.
The authors focus only on the Czech Republic due to the comparability of data. In particular,
government restrictions are specific for every single country, and due to different approaches to
restrictions travel behavior among countries cannot be objectively compared.
Table 2. Relative changes in the movement of people in specific localities in comparison with the usual
activity before the COVID-19 pandemic (Source: Google, 2020, edited by authors)
March 2020
Retail and
recreation
Grocery and
pharmacy
Parks
Transit
stations
Workplace
Residential
Prague
-77 %
-30 %
-58 %
-71 %
-38 %
+15 %
Moravian-
-Silesian
Region
-72 %
-21 %
- 14%
-63 %
-27 %
+10 %
Table 3. Relative changes in the movement of people in specific localities in comparison with the usual
activity before the COVID-19 pandemic (Source: Google, 2021, edited by authors)
March 2021
Retail and
recreation
Grocery and
pharmacy
Parks
Transit
stations
Workplace
Residential
Prague
-63 %
+4 %
-30 %
-50 %
-19 %
+12 %
Moravian- -
Silesian
Region
-62 %
-1 %
-19 %
-45 %
-4 %
+9 %
Based on Table 1, it can be concluded that comparison between the capital city of Prague and the
Moravian-Silesian Region, the fluctuation compared to the pre-COVID period is more pronounced in
Prague (variance for March 2020: 0.095 and March 2021: 0.072) than in the Moravian-Silesian Region
(variance for March 2020: 0.080 and March 2021: 0.064).
We have established the hypothesis that there is less passenger turnover in the Moravian-Silesian
Region than in the capital city of Prague with regard to the economic sector and the social status of the
region. The hypothesis is based on the different sectoral structure of the economy of compared regions
– the Moravian-Silesian Region is mostly oriented to industry and Prague is mostly oriented to the
tertiary sector of services. The hypothesis of a smaller fluctuation in the Moravian-Silesian Region is
confirmed by data on the number of passengers in regional bus transport. Backbone lines between
Ostrava and Frýdek-Místek in the Moravian-Silesian Region was analyzed. The assessed ratio of regional
bus transport between the cities of Ostrava and Frýdek-Místek decreased the number of passengers by
58.6% compared to the usual state. As a usual state authors used data set from 13.1.2020 to 17.1.2020.
The authors used data set from the peak of the second wave of the COVID-19 pandemic, from 2.11.2020
to 6.11.2020, as a COVID period. Compared to the capital of Prague (decrease in the number of
passengers in bus transport by 63% in Prague), a smaller decrease in the number of passengers is
evident. Procedures leading to ensuring safe and reliable public transport during the COVID-19
pandemic were applied on these bus lines.
2.3. Determination of safe vehicle capacity
While maintaining such spacing in public transport, this condition leads to a significant reduction in the
capacity of the vehicles offered. This creates a new value that can be described as the minimum number
of passengers to ensure safe transport in the spread of respiratory restrictions (Gkiotsalitis, 2021,
Hörcher et al., 2021).
Based on the performed literature review, it is possible to identify the basic requirements for safe and
credible public transport. The wearing of surgical masks or respirators can undoubtedly be identified as
a basic way of protecting passengers' health (Zhang et al., 2021). In particular, securing the distances
between individual passengers during their journey by public transport vehicles can be considered as an
accompanying measure to help reduce the remaining risk. Recommended physical distancing is at least
6 feet, which is equal to 1.83 meters (CDC, 2021b). To ensure the physical distance between passengers,
it is necessary to recalculate the maximum occupancy of the vehicle.
A comparison of the results of study about the long-distance trains in China (Hu et al., 2021) and the
study about spreading coronavirus in the urban bus (Zhang et al., 2021) reveals a different approach to
coronavirus infection. While the study of the urban bus environment is focused on the movement of
aerosol particles, the study of the probability of infection in individual seats in relation to the infected
passenger was based on data on 2334 infected passengers and their close contacts.
Additionally, the environment of an urban bus and a long-distance train is considerably different in its
configuration. The urban bus is characterized by its spaciousness, minimal division of space by partitions
or other objects and overall easy passage of air through the vehicle environment. Long-distance trains
are characterized by arranging the seats one behind the other, the individual rows of seats are
separated by tall backrests, and the flow of air in the space is thus limited.
The authors of this article have the ambition to ensure a safe and trustworthy environment in regional
buses and trains. The environment of these vehicles can be characterized as a combination of the urban
bus and long-distance train configuration. Compared to vehicles in urban transport, vehicles in regional
transport are equipped with a larger number of seats, which usually have higher backrests. The one
behind the other arrangement of seats is often used in buses dedicated to regional transport. The vis-à-
vis arrangement of seats is often used for regional train units. An analysis of the vehicle fleet in the
Moravian-Silesian Region was performed, and it was found that 95.08% of cars have a mostly vis-à-vis
arrangement and only 4.92% of vehicles have a balanced seats arrangement (partly vis-à-vis and partly
one behind the other) (KODIS, 2021a). It can be assumed that the free flow of air inside the vehicle will
be partially prevented by dividing the interior by the seat backrests. Nevertheless, vehicles intended for
regional transport will continue to be more spacious than long-distance vehicles, ie. the individual rows
of seats will not be carefully separated as well as in long distance arrangements. Compared to long-
distance transport, regional transport vehicles have advantage, namely, the shorter average time spent
in the vehicle.
With reference to the study (Hu et al., 2021), wherewith each additional hour the risk of infection in an
adjacent seat is 1.5% higher, it can be concluded that for journeys of up to 30 minutes there should not
be a higher risk of transmission than in the study (Hu et al., 2021). The findings of the study (Zhang et al.,
2021) are positive, because with use of surgical masks and a travel time up to 15 minutes, there was no
exposure to the virus, which would cause infection of other passengers.
From the above-described point of view, the author team approached the definition of a safe distance,
which is a key element in the prevention of COVID-19 virus infection, but is still conditioned by surgical
masks, as follows:
• It is not permissible to occupy adjacent seats, as this is the riskiest place in the vehicle,
• In the case of vis-à-vis seating arrangements, it is not permissible to occupy a seat on opposite
seats,
• In the case of aerial seating and full back arrangements, it is possible to seat two passengers in a
row,
• Sitting is prohibited at a distance of 6 feet (1.83 metres) from the driver's head - a safe zone is
created around the driver’s seat,
• In clear space, the minimum distance between the seating positions is 6 feet 1.83 metres), the
reference point being the presumed position of the mouth and nose on the seat in question.
Given the small difference in the seat spacing of vehicles in regional transport, these rules can be
generalized to all types of vehicles used in regional transport, both bus and tram or rail vehicles.
It is clear from the above rules that this will lead to a significant reduction in the standard capacity of the
vehicle. This results in the determination of the recalculated vehicle capacity, which is called the safe
vehicle capacity for the purposes of this study.
The value of this new capacity must be determined by the standardized vehicle configurations from the
floor plans of the individual vehicles. Subsequently, it is proposed to monitor the relationship between
standard capacity and recalculated capacity. The aim should be to determine the γmax coefficient, which
represents the maximum occupancy rate, which is the ratio of the allowable number of passengers to
capacity (Rüger, 1984).
2.4. Determination of the operational frequency to ensure safe transport
We propose a suitable frequency of service by the procedure of determining the frequency of service
depending on the number of passengers according to (Rüger, 1984). To determine the required supply
of seats in time, we consider the input values of the standard capacity of one car K, the maximum
degree of occupancy γmax and the force of transport current Q expressed in the number of persons per
time unit. The output of the specified procedure is then the required number of cars to provide service
in a given direction and per time unit F.
, (1)
Ffrequency of operation per direction [connections / time unit]
K vehicle capacity [offered seats]
Q passengers flow [persons / time unit]
γmax coefficient of maximum occupancy [-]
In the case of using the calculation in regional bus transport or where the service is provided only by
single-vehicle train units, the number of cars F can be considered as the frequency of service f.
f = F (2)
In cases where the composition of the train units is not variable and the train units are multiple, the
required frequency of service is obtained as follows:
, (3)
where n is the number of wagons of the train unit.
In cases where the composition of the train multiple units is diverse, determining the frequency of
service depending on the number of passengers is complicated. The frequency of operation is then
obtained under the condition that the relative proportion of sets are constant over time, as follows:
,
(4)
where k is the number of sets included in the composition calculation and n1, n2,…, nk is the number of
sets cars 1 to k.
In other cases, it is necessary to approach the assessment individually and to consider the specific
conditions of the case.
2.5. Comparison of daily variation before and during the COVID-19 pandemic
These capacities (standard and recalculated) will be used to verify the relative occupancy in the period
before and during the COVID-19 pandemic. From the obtained comparisons, it is then possible to
conclude whether it is possible to observe safe distances in public transport, or what the order of the
sets would have to be or how the scope of ordered transport would have to change to comply with the
distances. It is assumed that the individual measures will differ during the day, as it can be concluded
from the assessed data that due to government restrictions. The variation in the demand for transport
during the day has changed significantly. The measures taken have a significant effect on the daily
rhythm of passengers, with the vast majority of journeys being commuting and the peaks being shorter
and more intense than before COVID-19 (Anzai et al., 2021).
Data from the period before the first wave of the COVID-19 pandemic is considered the usual level,
which corresponds to the provided data from the period from 13.1.2020 to 17.1.2020. Data distortion
due to school holidays, public holidays or other macroscopic influences is not expected during this
period.
The period significantly affected by the COVID-19 pandemic can be considered the period from
2.11.2020 to 6.11.2020, when the second wave of the pandemic culminated (MZČR, 2020), at the same
time there was no data distortion due to public holidays. To clarify the form of the measures in the 2nd
wave of the COVID-19 pandemic, key measures concerning the restriction of the mobility of the
population are also listed.
In this case, we decided to compare the above-mentioned periods regarding the pandemic waves.
Second period was in the pandemic period when government regulations were in force. These
regulations had a very significant effect on the travel behavior of the population and emphasis was
placed on comparing data from the period with serious impact. In the given situation, these
representative time series describe the situation before and at the peak of the COVID-19 crisis. It is also
necessary to state that data from the other time periods from previous years contain seasonal
inequalities caused by public holidays, mass events and preparing for Christmas celebrations. Due to
government regulations the influence of Christmas shopping, mass events and public holidays is
recognizable, because activities connected with it were restricted.
In the selected period, the Government of the Czech Republic declared a state of emergency. Primary
schools, secondary schools, and universities were closed, and teaching occurred in a distance form.
Restaurants, retail, services, leisure, culture, and sports were also closed in most cases. Only health
services and grocery stores and other necessary assortments remained open. Industrial production was
almost unlimited. A curfew was introduced between 21:00 and 05:00, except for travel to or from work
(VLÁDA ČR, 2020a, VLÁDA ČR, 2020b, VLÁDA ČR, 2020c, VLÁDA ČR, 2020d).
3. Results
We defined the research task: We want to assess the seating arrangement in the interior of vehicles,
with an emphasis on creating a space that will have a positive effect on reducing the transmission of
respiratory infection. The aim is to restore passenger confidence in public transport and to restore
confidence in safe commuting on public transport vehicles.
The authors of the research applied the described methods to determine the γmax coefficient to
determine safe vehicle capacity. The authors assessed the γmax coefficient for a suburban bus and for a
characteristic suburban railway car or part of a multiple unit.
3.1. Determination of safe vehicle capacity
The rules defining the safe distance during public transport have been taken over from the Methods
section:
• It is not permissible to occupy adjacent seats, as this is the riskiest place in the vehicle
• In the case of vis-à-vis seating arrangements, it is not permissible to occupy a seat on opposite
seats
• In the case of an aerial arrangement of seats and full back, it is possible to seat two passengers
in a row
• Sitting is prohibited at a distance of 6 feet (1.83 metres) from the driver's head - a safe zone is
created around the driver
• In clear space, the minimum distance between the seating positions is 6 feet (1.83 metres), the
reference point being the presumed position of the mouth and the nose on the seat in question.
Given the small difference in the seat spacing of vehicles in regional transport, these rules can be
generalized to all types of vehicles used in regional transport, both bus and tram or rail vehicles. To
assess the impact of this measure in real operation, model vehicles were chosen. These are widely used
in regional transport in the Czech Republic.
The IVECO Crossway LE Line 12M (IVECO, 2020) was chosen as a model regional bus. The vehicle of this
configuration has a length of 12 meters, a two-door layout, and 45 seats, which are with tall backrests
(Lineo type).
The application of the defined rules selected the places near the window because they are the most
distant from each other within one row of seats. In the suburban bus, full back seats are usually used.
Due to this feature we can occupy seats in all rows in rear part of the vehicle. The individual rows of
seats are sufficiently separated by the backrests of the seats. For this reason, it is possible to shorten the
safe spacing distance, because with sufficient row separation, the risk of droplet spread is significantly
lower (Hu et al., 2021). In the rear of the car, one row of seats has been omitted, as there is unevenness
in height and there is no seat back protection from the previous row (the passenger would exhale
directly on the passenger's head in front of him). The first row of seats in the bus is also omitted,
because it is in the driver's safety zone. By applying the rules for determining safe seating positions with
a view to reducing the risk of COVID-19 infection, a total of 16 seats were identified in the vehicle. The
number of marked seating positions is based on the interior configuration of the vehicle, as shown in
Figure 2.
Figure 2. Scheme of a regional bus (Source: IVECO, 2020, edited by authors)
A similar recalculation principle can also be applied to regional rail vehicles. Single-decker multiple units
are widely used in regional rail transport, with 640 and 650 series vehicles being used as models (Škoda
Transportation, 2020). Although it is not a standardized vehicle in terms of exclusive representation of
vis-à-vis arrangement, the selected series of railway vehicles have a characteristic arrangement of seats
in terms of spacing. These vehicle series are suitable for demonstrating the need of occupancy reduction
in Czech conditions.
The 650 series unit is a two-car single-deck electric unit with a total capacity of 147 seats. The vehicle is
made with aisle between seats, a significant part of the seats is in a vis-à-vis configuration and tall
backrests design. The application of the defined rules selected the places near the window because they
are the most distant from each other within one row of seats. Regarding the use of seats with tall
backrests, the seats have been occupied in each row. In the case of a vis-à-vis arrangement, only one is
selected from each of the four seats. In places where the space is open or the seats are arranged
longitudinally, a rule of a minimum spacing of 6 feet (1.83 meters) between the seats has been applied.
By applying the rules for determining safe seating positions with a view to reduce the risk of COVID-19
infection, a total of 47 seating positions were identified in the 650 Series vehicle. Thus, for a typical
regional two-car unit, the original capacity of 147 seats was converted to a safe vehicle capacity of 47
seats. The number of marked seating positions depends on the inner layout of the vehicle, as shown in
Figure 3 (Škoda Transportation, 2020).
Figure 3. Scheme of regional train unit 650 (Source: Škoda Transportation, 2020, edited by authors)
The 640 series unit is a three-car single-deck electric unit with a total capacity of 241 seats. The vehicle is
made with aisle between seats, a significant part of the seats is in a vis-à-vis configuration and tall
backrests design. The application of the defined rules selected the places near the window because they
are the most distant from each other within one row of seats. Regarding the use of seats with tall
backrests, the seats have been occupied in each row. In the case of a vis-à-vis arrangement, only one is
selected from each of the four seats. In places where the space is open or the seats are arranged
longitudinally, a rule of a minimum spacing of 6 feet (1.83 meters) between the seats has been applied.
By applying the rules for determining safe seating positions with a view to reduce the risk of COVID-19
infection, a total of 74 seating positions were identified in the 640 Series vehicles. Thus, for a typical
regional three-car unit, the original seating capacity of 241 was converted to a safe vehicle capacity of
74 seats. The number of marked seating positions depends on the inner layout of the vehicle, as shown
in Figure 4 (Anzai et al., 2020).
Figure 4. Scheme of regional train unit 640 (Source: Škoda Transportation, 2020, edited by authors)
The monitored parameter is the γmax coefficient, which represents the maximum occupancy rate, which
is the ratio of the allowable number of passengers to capacity. Table 3 shows the values of standard
capacity and recalculated capacity, from which the value of the γmax coefficient is subsequently obtained
by calculation.
Table 3. Values of capacity and γmax coefficient (Source: authors)
Type of vehicle
Standard capacity
Safe capacity
γmax coefficient
Regional bus
45
16
0,356
Train unit No. 650
147
47
0,320
Train unit No. 640
241
74
0,307
Table 3 shows that the γmax coefficient varies from vehicle to vehicle. The main determining parameter
of the γmax coefficient is the arrangement of the seats in the vehicle. Regarding the rules set out in the
Methods chapter and adherence to the recommended spacings, only one of the four seats can be used
when arranging the seats vis-à-vis, while one of the two seats offered can be used when arranging the
seats in a row. It follows from the above that if the interior consisted only of seats in a vis-à-vis
arrangement, the γmax coefficient could take on a maximum value of 0.250. If the seats are arranged in a
row, a γmax factor of up to 0.500 could ideally be achieved. It can be seen from Figure 1 that in a regional
bus, the seating arrangement behind it predominates, while in train unit no. 640 is used to the
maximum extent possible in a vis-à-vis arrangement.
3.2. Determination of the operational frequency to ensure safe transport
In the model case, the relation of regional bus transport between the cities of Ostrava and Frýdek-
Místek was assessed. The assessment included the lines of the Integrated Transport System of the
Moravian-Silesian Region ODIS, specifically lines 351, 353, and 980, which are operated in the same
connection between the mentioned cities (KODIS, 2021b). Data on passenger transport in the period
before the outbreak of the COVID-19 pandemic and during the 2nd wave of the COVID-19 pandemic in
the Czech Republic was analyzed.
The data provided for both periods were used to analyze the frequency of service. The frequency of
service was calculated for each operating hour separately to assess the compliance of the offered
capacity with the necessary capacity to ensure safe and reliable transport in different parts of the day.
Table 4 shows the average daily numbers of passengers in the relevant operating hour at the border of
the regional capital Ostrava. Subsequently, the theoretical frequency of service is calculated based on
the values given in Tables 4 and 5 - ie, the standard capacity of the regional bus of 45 seats, in the period
of the COVID-19 pan-demic, a γmax coefficient of 0.356 is applied. The Planned frequency of the service
column shows the number of connections in the respective operating hour according to the standard
timetable. The column Actual frequency of service shows the number of connections regarding the
introduced emergency measures in transport, which aimed to reduce the costs of public transport due
to a significant reduction in sales.
Table 4. Overview of the scope of operation and theoretical frequency of operation (Data source: KODIS,
2021b; edited by authors)
Direction to Ostrava
Operational hour
Passengers per hour
Theoretical
frequency of service
(f)
Planned frequency
of service in
11/2020
Real (Actual)
frequency of service
in 11/2020
4
9
0,56
1
1
5
97
6,08
5
5
6
66
4,1
5
4
7
52
3,24
6
4
8
23
1,43
3
3
9
22
1,36
2
2
10
17
1,08
2
2
11
18
1,11
2
2
12
28
1,74
2
2
13
27
1,68
3
2
14
37
2,3
3
3
15
36
2,25
3
2
16
35
2,16
3
2
17
40
2,51
4
4
18
10
0,64
1
1
19
12
0,76
1
1
20
11
0,69
1
1
21
10
0,61
1
1
22
3
0,19
1
1
23
2
0,14
1
1
Table 5. Overview of the scope of operation and theoretical frequency of operation (Data source: KODIS,
2021b; edited by authors)
Direction to Frýdek-Místek
Operational hour
Passengers per hour
Theoretical
frequency of service
(f)
Planned frequency
of service in
11/2020
Real (Actual)
frequency of service
in 11/2020
4
14
0,9
1
1
5
0
0
0
0
6
56
3,48
5
4
7
39
2,46
5
4
8
26
1,61
3
3
9
23
1,43
2
2
10
19
1,16
2
2
11
23
1,41
2
2
12
27
1,71
3
3
13
44
2,76
4
4
14
47
2,93
3
2
15
63
3,96
4
4
16
68
4,28
5
4
17
30
1,86
3
2
18
40
2,48
4
4
19
7
0,46
1
1
20
12
0,75
1
1
21
4
0,23
1
1
22
2
0,1
1
1
23
1
0,08
1
1
It is evident from Table 5 that by reducing the volume of traffic, the γmax coefficient was exceeded in
many operating hours, which is evident from the insufficient frequency of service. To ensure the
carriage of passengers at the recommended distances, it is necessary to provide at least as many
connections as indicated by the theoretical frequency of service. The frequencies of connections in the
respective operating hours are highlighted in bold when there is insufficient service in the assessed
session. For such connections, it is then appropriate to deploy more capacitive vehicles, if such vehicles
are available, or to increase the frequency of service on a given route to ensure the recommended
distances between passengers. Table 6 shows the values of the γ coefficient for individual connections
during the COVID-19 pandemic. The γ coefficient is the general occupancy coefficient, which is described
as the ratio of vehicle capacity K to the actual number of passengers in the vehicle (column “Passengers
per bus”).
Table 6. Loads of individual connections (γ coefficient) (Data source: KODIS, 2021b; edited by authors)
Direction to Ostrava
Direction to Frýdek-Místek
Arrival time
to Ostrava
Passengers per bus
Value of γ
Departure time
from Ostrava
Passengers per bus
Value of γ
4:31
9
0,200
4:33
14,4
0,320
5:01
22
0,489
6:10
11,8
0,262
5:26
19,2
0,427
6:18
16,6
0,369
5:36
20,2
0,449
6:35
17
0,378
5:40
17,8
0,396
6:40
CANCELLED
5:55
18
0,400
6:50
10,2
0,227
6:06
18,8
0,418
7:09
8,2
0,182
6:15
CANCELLED
7:10
6,8
0,151
With the note canceled, canceled connections are an extraordinary measure in transport. It can be
noted that the connections immediately preceding or immediately following the canceled connection
often have the value of the γmax coefficient exceeded. It follows from the above that in the assessed area
it can be clearly recommended to maintain the planned scope of transport to ensure the transport of
6:30
14,6
0,324
7:29
9,4
0,209
6:36
18,2
0,404
7:45
15
0,333
6:45
14
0,311
7:59
CANCELLED
7:00
CANCELLED
8:10
8,8
0,196
7:06
16,4
0,364
8:24
5,8
0,129
7:15
CANCELLED
8:40
11,2
0,249
7:30
11,4
0,253
9:10
11,4
0,253
7:36
15,6
0,347
9:40
11,4
0,253
7:56
8,4
0,187
10:10
9,2
0,204
8:00
10,4
0,231
10:40
9,4
0,209
8:26
8
0,178
11:10
12,6
0,280
8:30
4,4
0,098
11:40
10
0,222
9:01
7,4
0,164
12:10
10,6
0,236
9:36
14,4
0,320
12:19
3,2
0,071
10:06
6,4
0,142
12:40
13,6
0,302
10:36
10,8
0,240
13:15
12,4
0,276
11:06
7,2
0,160
13:26
14,6
0,324
11:36
10,6
0,236
13:50
8,8
0,196
12:06
11,4
0,253
13:59
8,4
0,187
12:36
16,4
0,364
14:15
11,6
0,258
13:16
13,4
0,298
14:31
CANCELLED
13:26
13,4
0,298
14:40
35,2
0,782
13:57
CANCELLED
15:01
16,4
0,364
14:06
10
0,222
15:10
12,2
0,271
14:36
17
0,378
15:31
19
0,422
14:57
9,8
0,218
15:40
15,8
0,351
15:06
12,8
0,284
16:01
14,2
0,316
15:36
23,2
0,516
16:10
14,4
0,320
15:57
CANCELLED
16:31
CANCELLED
16:06
16,6
0,369
16:40
26,4
0,587
16:36
18
0,400
16:59
13,4
0,298
16:57
CANCELLED
17:10
9,4
0,209
17:06
19,2
0,427
17:29
CANCELLED
17:16
5,2
0,116
17:40
20,4
0,453
17:36
10,2
0,227
18:00
11,4
0,253
17:50
5,6
0,124
18:10
9,2
0,204
18:36
10,2
0,227
18:29
9,6
0,213
19:36
12,2
0,271
18:40
9,4
0,209
20:28
11
0,244
19:30
7,4
0,164
21:21
9,8
0,218
20:30
12
0,267
22:49
3
0,067
21:40
3,6
0,080
23:31
2,2
0,049
22:20
1,6
0,036
23:18
1,2
0,027
passengers with the recommended intervals. Furthermore, the γmax coefficient is exceeded in the
direction of Ostrava at 5 o'clock in the morning.
3.3. Comparison of daily variation before and during the COVID-19 pandemic
It is interesting to compare the daily variations in the period before and during the COVID-19 pandemic.
The already known data sets from January 2020 and November 2020 were compared. Figures 5 and 6
show that the load distribution on the Ostrava – Frýdek-Místek route has undergone fundamental
changes. Regarding the closure of schools and a large part of retail and services, the decline in peak
travel periods and its shift to more marginal parts of the day is evident. The largest share of passengers
arrives in Ostrava before 6 am and leave Ostrava after 4 pm. The most obvious change in behavior
relates to the interrupted commuting to schools. Differences in daily variations are also substantiated by
the composition of passengers according to travel documents. In the period from 7 a.m. to 8 a.m. and in
the period between 1 p.m. and 3 p.m., students usually predominate, while now, according to the
composition of travel documents, adult passengers predominate.
Figure 5. Daily variation of passengers – direction to Ostrava (Data source: KODIS, 2021b, edited by
authors)
Figure 6. Daily variation of passengers – direction to Frýdek-Místek (Data source: KODIS, 2021b, edited
by authors)
Figures 7 and 8 show the absolute numbers of passengers in the respective direction. A very significant
flattening of the curve is evident, the most significant differences are in the period of transport peaks,
which are less significant in relation to the off-peak hours.
Figure 7. Passengers per hour – direction to Ostrava (Data source: KODIS, 2021b, edited by authors)
In Figure 7 the smallest loss of passengers is around 5 a.m., because COVID-19 restrictions have a
minimal impact on the industry. Currently, workers from large industrial enterprises dominate among
commuters because the morning shift usually begins at 6 a.m. This is followed by the most dramatic
decline throughout the day, associated with the lack of students and staff working in services and
administration, who often study or work from home. In other parts of the day, the loss of passengers is
rather proportional.
Figure 8. Passengers per hour – direction to Frýdek-Místek (Data source: KODIS, 2021b, edited by
authors)
4. Discussion
To ensure safe and reliable public transport, it is necessary to respect the value of the γmax coefficient.
The Results chapter shows several approaches to achieve this. In the event of a reduction in transport
demand, for example due to the introduction of measures related to the COVID-19 pandemic, a
reduction of the γ coefficient below the γmax level can be achieved in a relatively natural way.
A limitation of the research is the focus on suburban regional transport, which has its own specificities in
terms of commuting time and vehicle interior layout. Given the completely different passenger
movements in urban transport vehicles, these results cannot be objectively applied to public transport
vehicles. The findings are also applicable to a limited extent to long-distance rail transport.
4.1. Measures leading to meet the coefficient of safe transport
If the loss of passengers is significant and the value of the γ coefficient is significantly lower than γmax, it
is also possible to consider savings in costs incurred in providing public transport. In this case, it is
appropriate to reduce the value of F, ie the number of cars per time unit. The reduction can be achieved
in two ways, either by reducing the number of vehicles in the set (by shortening the train set or by using
a unit with fewer cars), or by reducing the frequency of connections per given time unit. In the first case,
a reduction in the capacity offered, and therefore in costs, can be achieved without a significant
reduction in services. In the latter case, there is a risk of overflowing some connections or losing
network connections (Falchetta and Noussan, 2020, Dedík et al., 2020).
The third option considered is then characterized by a less significant decrease in passengers or
maintaining their number or increase. In such a case, the γmax coefficient is significantly exceeded,
because we usually assume a significantly higher value of the γmax coefficient than in the period of the
COVID-19 pandemic. In this case, vehicles are overloaded, and it is necessary to find a way to reduce the
relative use of vehicles. In this case, it is possible to strengthen the set with additional cars or create new
connections. Both measures are associated with another significant increase in costs. There may be a
limit on infrastructure capacity or a shortage of vehicles.
4.2. Economic aspects of the proposed measures
From an economic point of view, the effort to comply with the recommended distances in public
transport is a significant intervention in the economics of traffic. The determination of the γmax
coefficient depends on the internal layout of the vehicle, with the usable capacity of the vehicle being in
the range of 0.250 to 0.500. The question is whether reducing transport efficiency is affordable in long-
term. The way of securing the financing of public transport also plays an important role here. The impact
is directly proportional to the share of revenues in the overall economic balance of the service. Services
with low revenue coverage, where the dominant part of the revenue consists of public transport
customer compensation, are not as fundamentally affected by the loss of sales as services that are
operated purely at the carrier's commercial risk. Despite more or less drastic revenue shortfalls, the
simple loss of passengers is only a shortfall on the revenue side.
In a situation where, on the contrary, there will be no significant decline in demand for transport, it will
be necessary to ensure the recommended spacing by strengthening the sets or adding connections. In
this case, there is a risk not only of a decrease in revenues, but also of an increase in costs.
These increased costs are difficult to justify economically but can be seen as part of a marketing
campaign aimed at returning passengers to public transport. The return of passengers to public
transport is essential, as the return of the modal split of public transport to the level of 2019 is one of
the biggest challenges of the post COVID-19 agenda.
The limits of the research can be considered to be the focus on selected regions of the Czech Republic.
Furthermore, the research focused only on selected types of vehicles, which, however, appropriately
represent a typical vehicle fleet in selected regions. The detail of the research is based on the current
state of knowledge that prevailed at the beginning of 2021. Detailed information on the effects of the
pandemic on the public transport sector is still not available, given the inertia of the public sector.
4.3. Other approaches to safe and credible public transport
From the point of view of a contactless and safe environment in the vehicle, it is necessary to approach
the process of check-in and stay in the vehicle with an innovative approach aimed at minimizing the
contact of passengers with surfaces inside the vehicle interior. It is necessary to focus on limiting the use
of buttons for opening and closing doors, (boarding doors and doors separating compartments for
passengers or toilets). Furthermore, we focus on the possibility of contactless check-in on the train using
modern methods of check-in using a mobile phone or payment card. These measures should follow the
recommendations for better targeted cleaning of vehicles, incl. surface disinfection - from nano spraying
to ozone disinfection of the vehicle interior.
5. Conclusion
In addition to the constraints associated with government regulations, there is a general lack of
confidence in the safety and credibility of public transport. A shift in user preferences towards less
crowded and more flexible transport solutions is highly probable. The perceived level of risk will be an
important factor in choosing the mode of transport.
Public transport operators and authorities face the challenging task of restoring confidence in public
transport. It must minimize the risk throughout the transport process, although the use of masks will
undoubtedly continue to be common for some time. The transport offer must be flexible enough to
meet the needs of passengers while maintaining a safe distance. New technological solutions will be
important and will include the introduction of contactless systems from cashless payments to automatic
control of doors or waste bins.
Currently, the development in the post COVID-19 period is difficult to predict. However, it can be
assumed that the importance of teleworking will increase, and the population momentum will probably
decrease after years of steady growth. Financing of public transport in the future is another challenge to
be concerned. If the trend of greater individualization of transport persists, it will be difficult to finance
public transport in its current form. Rising fare prices or a reduction in the range of transport services
will rather have negative effects, deepen the decrease in the modal split of public transport and become
a threat to sustainable mobility in the future.
The value of the γmax coefficient is closely related to the seat’s configuration in the interior of the
vehicle. A higher value of γmax coefficient is achieved by a seating arrangement in a row (as in airplanes),
than by a vis-à-vis seating arrangement.
From the previous chapters it can be concluded that it is advisable for operators and public transport
organizers to use vehicles with a higher γmax coefficient on capacity-exposed services. If there is a
possibility to arrange vehicle circuits alternatively, then assign vehicles with the highest γmax coefficient
on the busiest routes. This will maintain the perceived safety of suburban transport at a lower cost,
there is no need to strength train or add additional services.
At the same time, increasing the public funds invested to public transport is a real challenge for the
sustainability of public transport in its current form. Taking into account safe distance among
passengers, an increase in transport subsidies from public funds is almost inevitable, because in all cases
mentioned in Figure 1 sustainable public transport becomes much more dependent on public financial
sources. Whether they will be used to rehabilitate fares or they will be used to co-finance capacity
strengthening.
Acknowledgements and/or funding resources
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit
sectors.
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Petr Fridrišek: Conceptualization, Methodology, Data collection, Writing - Original Draft
Vít Janoš: Conceptualization, Methodology, Supervision, Validation, Writing - Original Draft
Declaration of interests
☒ The authors declare that they have no known competing financial interests or personal
relationships that could have appeared to influence the work reported in this paper.
☐The authors declare the following financial interests/personal relationships which may be considered
as potential competing interests:
Highlights
We focus on possible approaches to safe regional public transport during COVID-19.
We determine safe vehicle capacity coefficient.
We analyze impact of capacity reduction on common types of vehicles.
We discuss demanding financing of public transport in the case of vehicle capacity reduction.
